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p u b l i c stat i c Loca lDataStoreS lot Alloc ateNamedDataS lot ( st r i n g name ) ; p u b l i c s t a t i c Loca lDataStoreSlot AllocateDataSlot ( ) ;

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3 yi = a + b log xi uses the data set {log xi , yi } 4 yi = 1/(a + b 10 xi ) can be transformed into 1/yi = a + b 10 xi The linear model is then tted to the data set {10 xi , 1/yi } 5 The model yi = xi /(axi b) can be transformed into 1/yi = a b/xi

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When specifying a named slot, the name supplied must be unique, or else an Argume n t E x c e pt ion will be thrown In both cases, a Loc a l Da t a StoreSlot object will be returned In the case of Al loc ateDataS lot, you must save this object in order to access the slot If you lose it, you can't access the slot ever again For named slots, there is a method to look up the slot, though saving it can avoid unnecessary subsequent lookups

p u b l i c s t a t i c L o c a l DataSto reSlot GetNamedDataS lot ( st ri n g name ) ;

already Once a slot has been created, you may set and get data using the SetData and GetData static methods, respectively Each accepts a Loc a lDataStoreS lot as an argument, and enables you to store and retrieve references to any kind of object

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Data sets are often greatly in uenced by very large or very small observations; we explored this to some extent in 12 For example, suppose salaries in a small manufacturing plant are as follows: $12, 500, $13, 850, $21, 900, $26, 200, $65, 600 The mean of these salaries is $27,410, but four out of ve workers receive less than this average salary! The mean is highly in uenced by the largest salary The median salary (the salary in the middle or the mean of the two middlemost salaries when the salaries are arranged in order) is $21,900 We could even replace the two highest salaries with salaries equal to or greater than $21,900, and the median would remain at $21,900 while the mean might be heavily in uenced

Creating a Payroll System / 11

p u b l i c s t a t i c obj e c t GetDat a ( Loca lDataStoreS lot s l ot ) ; p u b l i c s t a t i c void SetDat a ( Loca lDataStoreSlot s lot , o b j e c t d a t a ) ;

Last, it is important to free named slots when you no longer need them with the Thread class's F reeNamedDa t a S l ot static method

p u b l i c s t a t i c void F reeNamedDataS lot ( st r i n g n a me ) ;

For this reason, the median is called a robust statistic since it is not in uenced by extremely large (or small) values The median can also be used in regression We now describe the median median line This line is much easier to calculate than the least squares line and enjoys some surprising connections with geometry We begin with a general set of data {xi , yi } for i = 1, , n To nd the median median line, rst divide the data into three parts (which usually contain roughly the same number of data points) In each part, determine the median of the x-values and the median of the y-values (this will rarely be one of the data points) These points are then plotted as the vertices of a triangle P1 contains the smallest x-values, P2 contains the middle x-values, and P3 contains the largest x-values The median median line is determined by drawing a line parallel to the baseline (the line joining P1 and P3 ) and at 1/3 of the distance from the baseline toward P2 The concept is that since P1 and P3 contain 2/3 of the data and P2 contains 1/3 of the data, the line should be moved 1/3 of the distance from the baseline toward P2 The general situation is shown in Figure 136

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